Automated visualization support for linked research data

Abstract

Finding, organizing and analyzing research data (i.e. publications) published in various digital libraries are often tedious tasks. Each digital library deploys their own meta-model and technology to query and analyze the knowledge (in further text, scientific facts) contained in research publications. The goal of the EU-funded research project CODE is to provide methods for federated querying and analysis of such data. To achieve this, the CODE project offers a platform, that extracts scientific facts from research data and integrates them within the Linked Data Cloud using a common vocabulary (i.e. meta-model). To support users in analyzing scientific facts, the project provides means for easy-to-use visual analysis. In this paper, we present the web-based CODE Visualization Wizard, which aims to analyze research data visually with an emphasis on automating the visualization process. The main focus of the paper lies on a mapping strategy, which integrates various vocabularies to facilitate the automated visualization process.